{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from copy import deepcopy\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1</td>\n",
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       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
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       "      <td>3</td>\n",
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       "      <th>4</th>\n",
       "      <td>5</td>\n",
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       "      <td>49</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
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       "      <td>4</td>\n",
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       "      <td>45</td>\n",
       "      <td>3</td>\n",
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       "      <th>195</th>\n",
       "      <td>196</td>\n",
       "      <td>2</td>\n",
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       "      <td>51744</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>197</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
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       "      <td>198</td>\n",
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       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199</td>\n",
       "      <td>4</td>\n",
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       "      <td>1</td>\n",
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       "      <td>3</td>\n",
       "      <td>3</td>\n",
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       "      <td>3</td>\n",
       "      <td>37</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>8424</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
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       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      编号  信用卡账户状态  信用卡到期期限  信用卡历史信息  贷款目的  活期账户余额  非活期账户余额  受雇佣状况  分期付款比例  \\\n",
       "0      1        4       10        2     2   10504        1      5       1   \n",
       "1      2        2        9        2     9    7256        1      2       3   \n",
       "2      3        4       16        4     3   10880        1      3       4   \n",
       "3      4        1        7        2     0    9624        2      5       3   \n",
       "4      5        1       49        4     1   50648        1      5       4   \n",
       "..   ...      ...      ...      ...   ...     ...      ...    ...     ...   \n",
       "195  196        2       21        2     1   51744        5      1       1   \n",
       "196  197        1       16        2     9    6448        1      3       4   \n",
       "197  198        2       14        4     3    7056        1      2       4   \n",
       "198  199        4       25        2     1   62512        1      4       3   \n",
       "199  200        1       16        2     3    8424        1      2       4   \n",
       "\n",
       "     婚姻与性别  ...  财产  年龄  其他分期付款计划  住房情况  信用卡数  工作状态  无工作的家庭成员人数  注册电话是否在使用  \\\n",
       "0        3  ...   3  19         3     2     1     3           2          1   \n",
       "1        4  ...   1  25         3     2     1     3           2          2   \n",
       "2        3  ...   2  30         3     2     2     3           2          1   \n",
       "3        3  ...   2  42         3     2     1     3           2          2   \n",
       "4        3  ...   4  45         3     3     2     3           2          2   \n",
       "..     ...  ...  ..  ..       ...   ...   ...   ...         ...        ...   \n",
       "195      1  ...   1  59         3     2     1     4           2          2   \n",
       "196      2  ...   2  21         3     2     1     2           2          1   \n",
       "197      3  ...   1  22         3     2     2     3           2          1   \n",
       "198      3  ...   3  37         3     2     1     4           2          2   \n",
       "199      4  ...   1  26         3     2     1     3           2          1   \n",
       "\n",
       "     是否为外国人  信用分类  \n",
       "0         2   NaN  \n",
       "1         2   NaN  \n",
       "2         2   NaN  \n",
       "3         2   NaN  \n",
       "4         2   NaN  \n",
       "..      ...   ...  \n",
       "195       2   NaN  \n",
       "196       2   NaN  \n",
       "197       2   NaN  \n",
       "198       2   NaN  \n",
       "199       1   NaN  \n",
       "\n",
       "[200 rows x 22 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv(r\"D:\\Desktop\\作业\\python\\数据处理与可视化\\数据可视化数据\\比赛\\大数据题目发布_高职组\\testing.csv\",encoding='gbk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "one = pd.read_csv(r\"D:\\Desktop\\作业\\python\\数据处理与可视化\\数据可视化数据\\比赛\\大数据题目发布_高职组\\training.csv\",encoding='gbk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Int64Index([662], dtype='int64')\n",
      "Int64Index([272], dtype='int64')\n",
      "Int64Index([280, 672], dtype='int64')\n",
      "Int64Index([263], dtype='int64')\n",
      "Int64Index([623], dtype='int64')\n",
      "Int64Index([263], dtype='int64')\n",
      "Int64Index([269, 285], dtype='int64')\n",
      "Int64Index([267], dtype='int64')\n"
     ]
    }
   ],
   "source": [
    "for i in one: #查看个个列所有缺失值\n",
    "    if len(one[~one[i].notnull()])!=0:\n",
    "        print(one[~one[i].notnull()].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>264</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>10744</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>623</th>\n",
       "      <td>624</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7448</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>差</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>264</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>10744</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>270</td>\n",
       "      <td>4.0</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5736</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>53</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285</th>\n",
       "      <td>286</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>27992</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>差</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267</th>\n",
       "      <td>268</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>12432</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>23</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      编号  信用卡账户状态  信用卡到期期限  信用卡历史信息  贷款目的  活期账户余额  非活期账户余额  受雇佣状况  分期付款比例  \\\n",
       "662  663      NaN       37        3     9   63840      5.0    2.0     4.0   \n",
       "272  273      1.0       11        4     0    8304      NaN    4.0     4.0   \n",
       "280  281      1.0       13        4     0   16968      1.0    NaN     4.0   \n",
       "672  673      2.0       25        2    10   90624      1.0    NaN     2.0   \n",
       "263  264      3.0        7        4     0   10744      1.0    5.0     NaN   \n",
       "623  624      2.0        7        1     0    7448      2.0    2.0     1.0   \n",
       "263  264      3.0        7        4     0   10744      1.0    5.0     NaN   \n",
       "269  270      4.0       25        3     0    5736      5.0    5.0     4.0   \n",
       "285  286      1.0       13        4     0   27992      1.0    3.0     3.0   \n",
       "267  268      4.0        7        4     3   12432      1.0    4.0     1.0   \n",
       "\n",
       "     婚姻与性别  ...   财产  年龄  其他分期付款计划  住房情况  信用卡数  工作状态  无工作的家庭成员人数  注册电话是否在使用  \\\n",
       "662    3.0  ...  3.0  26         3   1.0     2     3         2.0          2   \n",
       "272    3.0  ...  2.0  48         3   2.0     2     3         2.0          2   \n",
       "280    3.0  ...  2.0  29         3   2.0     2     3         2.0          1   \n",
       "672    3.0  ...  3.0  28         1   2.0     2     4         2.0          2   \n",
       "263    3.0  ...  NaN  45         3   2.0     2     3         1.0          1   \n",
       "623    NaN  ...  2.0  31         2   2.0     1     2         2.0          1   \n",
       "263    3.0  ...  NaN  45         3   2.0     2     3         1.0          1   \n",
       "269    4.0  ...  3.0  53         3   NaN     2     3         2.0          2   \n",
       "285    2.0  ...  1.0  28         3   NaN     2     3         2.0          1   \n",
       "267    2.0  ...  3.0  23         3   1.0     2     3         NaN          2   \n",
       "\n",
       "     是否为外国人  信用分类  \n",
       "662       2     差  \n",
       "272       2     好  \n",
       "280       2     好  \n",
       "672       2     差  \n",
       "263       1     好  \n",
       "623       2     差  \n",
       "263       1     好  \n",
       "269       2     好  \n",
       "285       2     差  \n",
       "267       2     好  \n",
       "\n",
       "[10 rows x 22 columns]"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loss = one.iloc[[662,272,280,672,263,623,263,269,285,267]]\n",
    "loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [],
   "source": [
    "one2 = deepcopy(one)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>编号</th>\n",
       "      <th>信用卡账户状态</th>\n",
       "      <th>信用卡到期期限</th>\n",
       "      <th>信用卡历史信息</th>\n",
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       "      <th>...</th>\n",
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       "      <th>其他分期付款计划</th>\n",
       "      <th>住房情况</th>\n",
       "      <th>信用卡数</th>\n",
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       "      <td>2.0</td>\n",
       "      <td>13</td>\n",
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       "      <td>9</td>\n",
       "      <td>6728</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
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       "      <th>3</th>\n",
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       "      <td>1.0</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>16976</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>38</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>2</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>好</td>\n",
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       "      <th>4</th>\n",
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       "      <td>1.0</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>17368</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
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       "      <td>好</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>795</th>\n",
       "      <td>796</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>49592</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>差</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>796</th>\n",
       "      <td>797</td>\n",
       "      <td>1.0</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>15896</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>差</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>797</th>\n",
       "      <td>798</td>\n",
       "      <td>1.0</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>18424</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>2</td>\n",
       "      <td>差</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>799</td>\n",
       "      <td>4.0</td>\n",
       "      <td>22</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>101440</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>29</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>差</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>800</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>51744</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>51</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>差</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>791 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      编号  信用卡账户状态  信用卡到期期限  信用卡历史信息  贷款目的  活期账户余额  非活期账户余额  受雇佣状况  分期付款比例  \\\n",
       "0      1      1.0       19        4     2    8392      1.0    2.0     4.0   \n",
       "1      2      1.0       10        4     0   22392      1.0    3.0     2.0   \n",
       "2      3      2.0       13        2     9    6728      2.0    4.0     2.0   \n",
       "3      4      1.0       13        4     0   16976      1.0    3.0     3.0   \n",
       "4      5      1.0       13        4     0   17368      1.0    3.0     4.0   \n",
       "..   ...      ...      ...      ...   ...     ...      ...    ...     ...   \n",
       "795  796      1.0       13        0     3   49592      1.0    3.0     4.0   \n",
       "796  797      1.0       25        2     3   15896      1.0    3.0     2.0   \n",
       "797  798      1.0       25        2     0   18424      1.0    5.0     4.0   \n",
       "798  799      4.0       22        4     0  101440      5.0    5.0     4.0   \n",
       "799  800      2.0       13        2     3   51744      5.0    1.0     2.0   \n",
       "\n",
       "     婚姻与性别  ...   财产  年龄  其他分期付款计划  住房情况  信用卡数  工作状态  无工作的家庭成员人数  注册电话是否在使用  \\\n",
       "0      2.0  ...  2.0  20         3   1.0     1     3         2.0          1   \n",
       "1      3.0  ...  1.0  35         3   1.0     2     3         1.0          1   \n",
       "2      2.0  ...  1.0  22         3   1.0     1     2         2.0          1   \n",
       "3      3.0  ...  1.0  38         3   1.0     2     2         1.0          1   \n",
       "4      3.0  ...  2.0  37         1   2.0     2     2         2.0          1   \n",
       "..     ...  ...  ...  ..       ...   ...   ...   ...         ...        ...   \n",
       "795    3.0  ...  2.0  27         3   1.0     2     3         2.0          2   \n",
       "796    3.0  ...  1.0  20         3   1.0     1     2         1.0          1   \n",
       "797    3.0  ...  1.0  44         3   2.0     1     3         2.0          1   \n",
       "798    3.0  ...  4.0  29         3   3.0     1     4         2.0          2   \n",
       "799    3.0  ...  4.0  51         3   2.0     1     4         2.0          2   \n",
       "\n",
       "     是否为外国人  信用分类  \n",
       "0         2     好  \n",
       "1         2     好  \n",
       "2         2     好  \n",
       "3         1     好  \n",
       "4         1     好  \n",
       "..      ...   ...  \n",
       "795       2     差  \n",
       "796       2     差  \n",
       "797       2     差  \n",
       "798       2     差  \n",
       "799       2     差  \n",
       "\n",
       "[791 rows x 22 columns]"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "one2 = one2.dropna(axis=0, how='any', subset=None,inplace=False)  #数据量小，删除了\n",
    "one2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "one_2 = one2.groupby(by='信用分类')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "cha = one_2.get_group('差')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "hao = one_2.get_group('好')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>住房情况</th>\n",
       "      <th>信用卡到期期限</th>\n",
       "      <th>信用卡历史信息</th>\n",
       "      <th>信用卡数</th>\n",
       "      <th>信用卡账户状态</th>\n",
       "      <th>其他分期付款计划</th>\n",
       "      <th>分期付款比例</th>\n",
       "      <th>受雇佣状况</th>\n",
       "      <th>婚姻与性别</th>\n",
       "      <th>居住时间</th>\n",
       "      <th>...</th>\n",
       "      <th>年龄</th>\n",
       "      <th>担保人</th>\n",
       "      <th>无工作的家庭成员人数</th>\n",
       "      <th>是否为外国人</th>\n",
       "      <th>注册电话是否在使用</th>\n",
       "      <th>活期账户余额</th>\n",
       "      <th>编号</th>\n",
       "      <th>财产</th>\n",
       "      <th>贷款目的</th>\n",
       "      <th>非活期账户余额</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>信用分类</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>好</th>\n",
       "      <td>1.947273</td>\n",
       "      <td>20.303636</td>\n",
       "      <td>2.665455</td>\n",
       "      <td>1.410909</td>\n",
       "      <td>2.865455</td>\n",
       "      <td>2.705455</td>\n",
       "      <td>2.952727</td>\n",
       "      <td>3.483636</td>\n",
       "      <td>2.703636</td>\n",
       "      <td>2.805455</td>\n",
       "      <td>...</td>\n",
       "      <td>35.389091</td>\n",
       "      <td>1.136364</td>\n",
       "      <td>1.860000</td>\n",
       "      <td>1.958182</td>\n",
       "      <td>1.396364</td>\n",
       "      <td>23379.374545</td>\n",
       "      <td>291.460000</td>\n",
       "      <td>2.270909</td>\n",
       "      <td>2.876364</td>\n",
       "      <td>2.312727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>差</th>\n",
       "      <td>1.875519</td>\n",
       "      <td>25.560166</td>\n",
       "      <td>2.174274</td>\n",
       "      <td>1.369295</td>\n",
       "      <td>1.892116</td>\n",
       "      <td>2.543568</td>\n",
       "      <td>3.029046</td>\n",
       "      <td>3.116183</td>\n",
       "      <td>2.560166</td>\n",
       "      <td>2.771784</td>\n",
       "      <td>...</td>\n",
       "      <td>32.647303</td>\n",
       "      <td>1.120332</td>\n",
       "      <td>1.850622</td>\n",
       "      <td>1.983402</td>\n",
       "      <td>1.381743</td>\n",
       "      <td>31272.298755</td>\n",
       "      <td>649.356846</td>\n",
       "      <td>2.551867</td>\n",
       "      <td>2.738589</td>\n",
       "      <td>1.597510</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          住房情况    信用卡到期期限   信用卡历史信息      信用卡数   信用卡账户状态  其他分期付款计划    分期付款比例  \\\n",
       "信用分类                                                                          \n",
       "好     1.947273  20.303636  2.665455  1.410909  2.865455  2.705455  2.952727   \n",
       "差     1.875519  25.560166  2.174274  1.369295  1.892116  2.543568  3.029046   \n",
       "\n",
       "         受雇佣状况     婚姻与性别      居住时间  ...         年龄       担保人  无工作的家庭成员人数  \\\n",
       "信用分类                                ...                                    \n",
       "好     3.483636  2.703636  2.805455  ...  35.389091  1.136364    1.860000   \n",
       "差     3.116183  2.560166  2.771784  ...  32.647303  1.120332    1.850622   \n",
       "\n",
       "        是否为外国人  注册电话是否在使用        活期账户余额          编号        财产      贷款目的  \\\n",
       "信用分类                                                                      \n",
       "好     1.958182   1.396364  23379.374545  291.460000  2.270909  2.876364   \n",
       "差     1.983402   1.381743  31272.298755  649.356846  2.551867  2.738589   \n",
       "\n",
       "       非活期账户余额  \n",
       "信用分类            \n",
       "好     2.312727  \n",
       "差     1.597510  \n",
       "\n",
       "[2 rows x 21 columns]"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "one2_1 = one2.pivot_table(index='信用分类',aggfunc='mean')\n",
    "one2_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-215-3392a2cd5734>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  one2['信用分类'] = pd.get_dummies(one2['信用分类'])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0      1\n",
       "1      1\n",
       "2      1\n",
       "3      1\n",
       "4      1\n",
       "      ..\n",
       "795    0\n",
       "796    0\n",
       "797    0\n",
       "798    0\n",
       "799    0\n",
       "Name: 信用分类, Length: 791, dtype: uint8"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "one2['信用分类'] = pd.get_dummies(one2['信用分类'])\n",
    "one2['信用分类']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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HgNGGkqiq1VW1tKqW9vf3T32lkjRLdSMM1rF1aGgJsGGUNmuSLEnSB6wAvt6FuiRJrW6EwWXAG5N8EHg98I0k7x3R5lxgDXATsLaqvtSFuiRJrY5P1FbVxiTLgWOA86rqHkZ88q+qW2lWFEmSeqArq3aq6kG2riiSJE0znoEsSTIMJEmGgSQJw0CShGEgScIwkCRhGEiSMAwkSRgGkiQMA0kShoEkCcNAkoRhIEnCMJAkYRhIkjAMJEkYBpIkDANJEoaBJAnDQJKEYSBJwjCQJGEYSJIwDCRJGAaSJAwDSRKGgSQJw0CShGEgSaJLYZDkgiRrk6zanjaSpM7oeBgkOQnoq6plwAFJFm9LG0lS53SjZ7AcuKS9fxVw1Da2kSR1yNwuvMauwF3t/QeAw7exDUlWAivbh5uSfHsK65yt9gLu63UR00Xe3+sKNAr/RofZzr/R/cfa0Y0w2AQsaO8vZPTeyGTaUFWrgdVTXeBslmSgqpb2ug5pLP6Ndkc3honWsXXYZwmwYRvbSJI6pBs9g8uAa5PsB7wG+PUk762qVeO0ObILdUmSWqmqzr9IsjtwDPCVqrpnW9to6iVZ2Q6/SdOSf6Pd0ZUwkCRNb56BPEsl2aPXNUiaPuwZzFJJbgReCewEvBDYMmz3uqr6YU8Kk4ZJsltVPdTe37uq7u11TTOVPYNZKMnOwJ1V9TBNGOwPLAJeAXwaeHrvqpMaSeYAVyfZs910RZLn9LKmmcyewSyT5Djg/cB84EfA6qr6myRLgA8Cv1NV3+tljVKSLwKbgX5gY7v5QOAWmg8wb3ShydTqxtJSTSNVdUWSlwJXA78AfL3ddQSwxiDQNHEKzZnHBVwEnA48BgR42CCYevYMZqEkXwF+EfgCcB1wLM1/PIB7gCur6gM9Kk8iyYto5rR2B44D/rHd1QfcXlWX96q2mcowmGWSzAUuBW4HnllVb2y3vwmgqi7sWXESkOTVwDtoegV70cxhrR/ehGZ487M9KG/GcpholqmqJ5P8Gs0lQNYnmV9Vj/e6LmmYq2muXvwsmiGiF1fVE/DjSeXQBIWmkKuJZpkkC4C/B84DrgTOaXftwk8uL5V6oqo20/QIPg18E7g8yQ+S/DtwBfDKqvJvdYo5TDTLJDkZYKiLnaQPeDNwKvAGJ5DVa0mOAP4B+N2qur7ddhFwTlV9p6fFzWCGgaRpJcnzaS5p/xbg2e3mA4E7gUdplkW/tar+szcVzkyGgSTJOQNJkmEgScIwkKZEu+RR2mH5ByxNUpKFSc5Nkvbx+nayE+Cvk/zusLYLkuw04vl97Ul/Q49fkeSabtQuTcQwkCYvwInAue3jx4HH2ksnnApcO6ztO4CbkzyS5KYk99F8t/fJbaAsbZ/vCX+aFgwDaZLa73h4HfArSeYP2/XHwJ9U1beGtT0X+GXg1qp6IfA54F1V9Sng+cBC4Ek80U/ThJejkCYhyeXAwcAmYB7wDZrvgLiS5kPVoUneATwNWAw8A9gD2JJkIc3/tQXtN8y5nlvTjmEgTc6KoUsgJDkG+AhwL/B64BPAGVV1Tbt/KXAxzclRuwE3APvRXB32l9l6KWZp2nCYSJqEqtrSTgqfDXyUZu7gYZovCDoH+FSSDyXZuaoGqup5wPk0V9c8BLgE+LOqWkFzHaidRn0hqUcMA2kSkpwCfAfYl+YqmrcD9wGbq+pfgcOBlwBnt+1/Dng7zVwBNL3w+QBVdUL7nJ1p5g2knnOYSJqctcAxVXXbsG1zgMOADVX1v0l+EZif5OnAvwH/VFVfbduuAeYm6auqzUlOpPnClvO6+DtIY/LaRNIkJLmBZnL4iXbTTsBBNL2Du4aatdt/k2aS+Dbg0faSzCT5AfCiqhpsLyV+EHBT+Z9Q04BhIG2DJO8DnkvTMzixqr49Spv/pgmHoQDZH/g+zXLSOTRX5jy8qu7uStHSOAwD6Sloh4DOBo4CjgZeQDME9GHg76vq0XGeuwF4YVX9XxdKlZ4SJ5ClSUjy5iRD3x39BM23bf2wqm4EltOEw11J1rSXmbi/vVzFd4ZuNF/uvm74tiT3JFnZs19MatkzkCahXU1UwJVV9dAYbQ4EXlpVF3azNmkqGAaSJIeJJEmGgSQJw0CShGEgScIwkCQB/w8ND7Kn+3PVIQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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QpBYN1eI/Hji/f34RcOxAdUhSc5YNdNzHADf3z78KHDV3hyQbgA394t1Jvjim2payA4Hbhi5id5G3DV2B5uF7dJZH+R59wkIbhgr+u4GV/fNVzPPNo6o2AhvHWdRSl2S6qqaGrkNaiO/R8Riqq+dKtnXvrAW2DFSHJDVnqBb/h4FLkxwKnAgcM1AdktScQVr8VXUX3QDv5cBzqurOIepokF1n2t35Hh2DVNXQNUiSxsgrdxuQ5ICha5C2J8l+s54fNGQtS50t/gYkuQJ4DrA38AzgoVmbr6yq/x2kMKmXZC+6rt8Tq+r2JJ8FXlxV/zlwaUvSUIO7GpMk+wA3VdU9SfalO7e3gMOAVwLPBAx+DSbJx4AH6d6X5yUBOAh4d5K9gZdW1a0Dlrjk2OJfwpL8EPA2YAXwDWBjVf1xkrXAO4GX26LS0JKsprtwq4C/AE4H7gMC3FNV/z1geUuSLf4lrKo+kuTZwCeAHwCu7jcdDWw29LWbOJyuK3I1XSNlfb9+ArgeuHCYspYuW/xLXJJPA88F/hb4DHASXesK4Fbgo1X1joHKU+OSPB94HV1r/0BgX+CG2bvQfVP9ywHKW7IM/iUsyTLgArpW03dU1Uv79T8NUFXvH6w4CUgyQRf6j6Pr5jmhqu7vt+1FF/xVVQ8t/Fu0szydcwmrqgeAHwWeB6xKsmLgkqRvUVUP0rX0PwT8K3Bhkv9K8vfAR+gu8DT0dzH7+JewJCuB9wBvB74NeDPwa/3zu4erTOokORp4H/CKqvqnft1fAG+uqi8NWtwSZlfPEpbkNICt/aP91+pfAF4C/LiDuxpakqfQzdT7GrpTjAGeDNwE3Es32PtLVfW5YSpcmgx+SWqMffyS1BiDX5IaY/BLUmMMfmkn9eeXS3ss38DSPJKsSnJ2+hnDktzQn4EC8PtJXjFr35X9ZGKzXz/RX0C3dfm4JJeMo3Zpewx+aX4BTgHO7pe/CdyX5HvpToe9dNa+rwOuSfL1JFcluY3uPtKn9R8eU/3rvzm26qVFGPzSPPp7FPwI8MNzrng+A/iVqvq3WfueTXd19LVV9Qzgr4Bfr6oPAk8BVgEP8K33QZAG45W70hxJLgSeRnd183LgOroZJD9K11g6IsnrgMcCa4D9gQOAh5Ksovu/Wtnf+cwLZbTbMfilhzt16/wwSdYDfwh8BXgx8GfAWVV1Sb99CjiP7grT/ejuInUo3Syoz2PbvPLSbsOuHmmOqnqoH7B9E/Buur7+e+huZvNm4INJ3pVkn6qarqonAefQTR/8dOB84Neq6lS6eZH2nvdA0kAMfmmOJD8BfAk4BHhmVV0P3AY8WFUfB44CngW8qd//e4DX0vXtQ/dNegVAVZ3cv2Yfun5+aXB29UgPdxmwvqq+MGvdXsCRwJaq+p8kzwVW9Pcx/iTw11X1z/2+m4FlSSaq6sEkpwB/TjdLqjQ4J2mT5khyOd3A7f39qr2B76Zr9d+8dbd+/cvoBnC/ANzbzy9Pkv8CvreqZvrpsb8buKr8h9NuwOCXtiPJW4Hvomvxn1JVX5xnn3+n+yDY+mHxBODLdKdw7kU39fBRVXXLWIqWFmHwSwvou3HeBBwLnAA8la4b5w+A91bVvYu8dgvwjKr62hhKlXaKg7vSHEl+IcnWexXfT3f7v/+tqiuA4+k+CG5OsrmfiuH2fkqHL239AVYDV85el+TWJBsG+8Okni1+aY7+rJ4CPlpVdy6wz5OBZ3vDeu2JDH5JaoxdPZLUGINfkhpj8EtSYwx+SWqMwS9Jjfk/C0DvZwrPdKMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['font.family']='SimHei'\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "for i in one2_1:\n",
    "    plt.bar(list(one2_1.index),one2_1[i])\n",
    "    plt.xlabel('类型',size=13)\n",
    "    plt.ylabel('数值',size=13)\n",
    "    plt.title(i)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>编号</th>\n",
       "      <th>信用卡账户状态</th>\n",
       "      <th>信用卡到期期限</th>\n",
       "      <th>信用卡历史信息</th>\n",
       "      <th>贷款目的</th>\n",
       "      <th>活期账户余额</th>\n",
       "      <th>非活期账户余额</th>\n",
       "      <th>受雇佣状况</th>\n",
       "      <th>分期付款比例</th>\n",
       "      <th>婚姻与性别</th>\n",
       "      <th>...</th>\n",
       "      <th>财产</th>\n",
       "      <th>年龄</th>\n",
       "      <th>其他分期付款计划</th>\n",
       "      <th>住房情况</th>\n",
       "      <th>信用卡数</th>\n",
       "      <th>工作状态</th>\n",
       "      <th>无工作的家庭成员人数</th>\n",
       "      <th>注册电话是否在使用</th>\n",
       "      <th>是否为外国人</th>\n",
       "      <th>信用分类</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>8392</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>22392</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>35</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>6728</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>16976</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>38</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>17368</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>590</th>\n",
       "      <td>591</td>\n",
       "      <td>2.0</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>22080</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>591</th>\n",
       "      <td>592</td>\n",
       "      <td>4.0</td>\n",
       "      <td>25</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>44056</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>43</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592</th>\n",
       "      <td>593</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>9592</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>66</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>593</th>\n",
       "      <td>594</td>\n",
       "      <td>3.0</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>23136</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>594</th>\n",
       "      <td>595</td>\n",
       "      <td>2.0</td>\n",
       "      <td>37</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>22896</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>29</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>好</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>550 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      编号  信用卡账户状态  信用卡到期期限  信用卡历史信息  贷款目的  活期账户余额  非活期账户余额  受雇佣状况  分期付款比例  \\\n",
       "0      1      1.0       19        4     2    8392      1.0    2.0     4.0   \n",
       "1      2      1.0       10        4     0   22392      1.0    3.0     2.0   \n",
       "2      3      2.0       13        2     9    6728      2.0    4.0     2.0   \n",
       "3      4      1.0       13        4     0   16976      1.0    3.0     3.0   \n",
       "4      5      1.0       13        4     0   17368      1.0    3.0     4.0   \n",
       "..   ...      ...      ...      ...   ...     ...      ...    ...     ...   \n",
       "590  591      2.0       25        2     1   22080      5.0    5.0     4.0   \n",
       "591  592      4.0       25        4     5   44056      1.0    5.0     3.0   \n",
       "592  593      2.0       10        2     6    9592      1.0    4.0     4.0   \n",
       "593  594      3.0       25        2     2   23136      1.0    5.0     3.0   \n",
       "594  595      2.0       37        3     0   22896      2.0    5.0     4.0   \n",
       "\n",
       "     婚姻与性别  ...   财产  年龄  其他分期付款计划  住房情况  信用卡数  工作状态  无工作的家庭成员人数  注册电话是否在使用  \\\n",
       "0      2.0  ...  2.0  20         3   1.0     1     3         2.0          1   \n",
       "1      3.0  ...  1.0  35         3   1.0     2     3         1.0          1   \n",
       "2      2.0  ...  1.0  22         3   1.0     1     2         2.0          1   \n",
       "3      3.0  ...  1.0  38         3   1.0     2     2         1.0          1   \n",
       "4      3.0  ...  2.0  37         1   2.0     2     2         2.0          1   \n",
       "..     ...  ...  ...  ..       ...   ...   ...   ...         ...        ...   \n",
       "590    3.0  ...  4.0  35         1   3.0     1     3         2.0          2   \n",
       "591    3.0  ...  4.0  43         3   3.0     2     3         2.0          1   \n",
       "592    2.0  ...  2.0  66         3   2.0     2     4         2.0          2   \n",
       "593    1.0  ...  4.0  50         3   3.0     1     3         2.0          1   \n",
       "594    3.0  ...  4.0  29         3   3.0     1     3         2.0          1   \n",
       "\n",
       "     是否为外国人  信用分类  \n",
       "0         2     好  \n",
       "1         2     好  \n",
       "2         2     好  \n",
       "3         1     好  \n",
       "4         1     好  \n",
       "..      ...   ...  \n",
       "590       2     好  \n",
       "591       2     好  \n",
       "592       2     好  \n",
       "593       2     好  \n",
       "594       2     好  \n",
       "\n",
       "[550 rows x 22 columns]"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hao"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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